Short Description
open_iA is a modular open source software tool for the visual analysis and processing of volumetric datasets, with a focus on industrial computed tomography datasets.
open_iA can open and process a variety of volume and surface datasets. For displaying such datasets, it offers classical 2D slice views and adjustable 3D renderings, both with interactive navigation, as well as histograms and line profiles. For processing datasets it offers a variety of methods, mainly targeted at volume data, such as for segmentation, the extraction of characteristics as well as registration. These processing methods are also available from the command line. Additionally, open_iA comes with modules which provide support for specific analysis scenarios. Among those are specialized visualization methods for the distribution of fiber characteristics, several tools for a comparative analysis of the parameter and result space of different image processing algorithms, as well as tools for immersive analytics of datasets in augmented and virtual reality, as well as machine learning. open_iA is easily extensible and serves as the central development platform of the research group computed tomography at the University of Applied Sciences Upper Austria, Wels Campus.
Links:
https://3dct.github.io/open_iA
https://www.youtube.com/@open_iA
https://forschung.fh-ooe.at/en/about-research/researchgroups/computed-tomography/
Citation:
Bernhard Fröhler, Johannes Weissenböck, Marcel Schiwarth, Johann Kastner, and Christoph Heinzl, open_iA: A tool for processing and visual analysis of industrial computed tomography datasets, Journal of Open Source Software, 4 (35), 2019, 1185, doi: 10.21105/joss.01185.
Contact Person
Bernhard Fröhler
Research Services
Application and development of algorithms, technologies and methods for visual analysis (with a focus on X-ray computed tomography) using complex data from a wide variety of domains.
Methods & Expertise for Research Infrastructure
Tailored filters, analysis modules and visualization techniques for the visual analysis of complex industrial X-ray computed tomography data
Land OÖ FTI X‑Pro: Erforschung und Entwicklung benutzer‑zentrierter Methoden für Cross‑Virtuality Analytics von Produktionsdaten (2020 ‑ 2024), 1 Partners, 1 Country, https://x-pro.fh-ooe.at/
Dissertationsprogramm der FHOÖ 2020, AugmeNDT ‑ Immersive On‑Site and Remote Analysis of Complex Composite Materials using Augmented Reality Techniques (2020 ‑ 2023), 4 Partners, 2 Countries
Dissertationsprogramm der FHOÖ 2020, COMPARE ‑ Comparative Analysis of Temporal Trends in Multidimensional Data Ensembles from Materials Testing (2020 ‑ 2023), 4 Partners, 2 Countries
FFG Takeoff BeyondInspection: Digitalisierungsplattform zur prädiktiven Bewertung von Luftfahrtbauteilen mittels multimodaler multiskalarer Inspektion (2019 ‑ 2022), 4 Partners, 1 Country, http://www.3dct.at/beyondinspection
A. Gall, B. Fröhler, J. Maurer, J. Kastner, and C. Heinzl, Cross-Virtuality Analysis of Rich X-Ray Computed Tomography Data for Materials Science Applications, Nondestructive Testing and Evaluation, doi: 10.1080/10589759.2022.2075864; presented at 11th International Conference on Industrial Computed Tomography (ICT)).
A. Gall, E. Gröller, C. Heinzl, ImNDT: Immersive Workspace for the Analysis of Multidimensional Material Data From Non‑Destructive Testing, In ACM Symposium on Virtual Reality Software and Technology (VRST) 2021, Osaka / Japan, 2021, pp. 11, doi:10.1145/3489849.3489851
A. Heim, E. Gröller, C. Heinzl, CoSi: Visual Comparison of Similarities in High‑Dimensional Data Ensembles, In Vision, Modeling, and Visualization (2021), VMV 2021, Dresden / Germany, 2021, pp. 8, doi:10.2312/vmv.20211378
B. Fröhler, T. Elberfeld, T. Möller, H.-C. Hege, J. Weissenböck, J. De Beenhouwer, J. Sijbers, J. Kastner, C. Heinzl, A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science, Computer Graphics Forum, 38 (3), 2019, pp. 273–283, doi: 10.1111/cgf.13688.
J. Weissenböck, B. Fröhler, E. Gröller, J. Kastner, C. Heinzl, Dynamic Volume Lines: Visual Comparison of 3D Volumes through Space-filling Curves, Transactions on Visualization and Computer Graphics, 25 (1), 2018, pp. 1040–1049, doi: 10.1109/TVCG.2018.2864510.
A. Amirkhanov, A. Amirkhanov, D. Salaberger, J. Kastner, E. Gröller, C. Heinzl, Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests, Computer Graphics Forum, 35 (3), 2016, pp. 201–210, doi: 10.1111/cgf.12896.
B. Fröhler, T. Möller, and C. Heinzl, GEMSe: Visualization-Guided Exploration of Multi-channel Segmentation Algorithms, Computer Graphics Forum, 35 (3), 2016, pp. 191–200, doi: 10.1111/cgf.12895.
J. Weissenböck, A. Amirkhanov, W. Li, A. Reh, A. Amirkhanov, E. Gröller, Johann Kastner, C. Heinzl, FiberScout: An Interactive Tool for Exploring and Analyzing Fiber Reinforced Polymers, IEEE Pacific Visualization Symposium, Yokohama, 2014, pp. 153–160, doi: 10.1109/PacificVis.2014.52.
A. Amirkhanov, B. Fröhler, J. Kastner, E. Gröller, C. Heinzl, InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data, Computer Graphics Forum, 33 (3), 2014, pp. 91–100, doi: 10.1111/cgf.12365.